Data Mining and Service Customization in Leisure and Hospitality
I A. Kamani C Samarasinghe1, Saluka Kodituwakku2, Roshan D. Yapa3
1I A K C Samarasinghe, Post Graduate Institute of Science, University of Peradeniya, Peradeniya, Sri Lanka.
2S. R Kodithuwakku, Department of Statistics & Computer Science, Faculty of Science, University of Peradeniya, Peradeniya, Sri Lanka.
3S.D Yapa, Department of Statistics & Computer Science, Faculty of Science, University of Peradeniya, Peradeniya, Sri Lanka.
Manuscript received on October 09, 2013. | Revised Manuscript received on October 29, 2013. | Manuscript published on November 05, 2013. | PP: 24-29 | Volume-3 Issue-5, November 2013 . | Retrieval Number: E1858113513 /2013©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This study provides insights into the relationship between data mining activities and the customization of the packages offered to tourists by hotels. Data mining provides a method of understanding the needs and habits of the tourists so that hotels can provide targeted value propositions to tourists from different geographies. For the study, ten prominent hotels around the country were selected and three employees from each hotel with information were interviewed to collect information about the data mining activities they perform. The study identifies that hotels give a high level of attention to data mining. Many of the hotels have suitable systems to capture the data of the guests, and have suitable staff to operate them. This indicates that data mining capabilities are either being built or are already in place in many of the hotels. It is also seen that hotels actively seek to customize the packages they offer to customers. All these eventually result in increased levels of long term customer loyalty. The regression analysis indicated a very strong relationship between data mining and the customization of service packages. The also study indicates that there is a significant correlation between the data mining activities of the hotels and the customized value and service offerings. This indicates that the hotels of the country are using data mining to develop customized service offerings. This is likely to benefit the hotels as well as Sri Lanka as a whole due to increased repeat visits by the tourists.
Keywords: Customized service packages, Data mining, , Hotels, Tourism.
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